Evidence map›Paper›PMID 33781274›Full record

ArticleGlobalization and health2021

Does the medical insurance system play a real role in reducing catastrophic economic burden in elderly patients with cardiovascular disease in China? Implication for accurately targeting vulnerable characteristics.

Meiyan Ma, Wanxin Tian, Jian Kang, Yuze Li, Qi Xia, Nianshi Wang, Wenqing Miao, Xiyu Zhang, Yiyun Zhang, Baoguo Shi and 8 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Globalization and health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 pooled it
8.2field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 45 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 7 institutions in 1 country.

Meiyan MaResearch Center of Public Policy and Management, School of Health Management, Harbin Medical University, Harbin, 150086, Heilongjiang, China.
Wanxin TianResearch Center of Public Policy and Management, School of Health Management, Harbin Medical University, Harbin, 150086, Heilongjiang, China.
Jian KangHeilongjiang Provincial Hospital, Harbin, Heilongjiang, China.
Yuze LiDepartment of Medicine, Jiamusi University, Jiamusi, 154007, Heilongjiang, China.
Qi XiaResearch Center of Public Policy and Management, School of Health Management, Harbin Medical University, Harbin, 150086, Heilongjiang, China.
Nianshi WangResearch Center of Public Policy and Management, School of Health Management, Harbin Medical University, Harbin, 150086, Heilongjiang, China.
Wenqing MiaoResearch Center of Public Policy and Management, School of Health Management, Harbin Medical University, Harbin, 150086, Heilongjiang, China.
Xiyu ZhangResearch Center of Public Policy and Management, School of Health Management, Harbin Medical University, Harbin, 150086, Heilongjiang, China.
Yiyun ZhangSchool of Ethnology and Sociology, Yunnan University, Kunming, Yunnan, China.
Baoguo ShiDepartment of Economics, School of Economics, Minzu University of China, Beijing, China.
Han GaoThe Affiliated Tumor Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Tao SunDepartment of Health Service Management, School of Medicine, Hang Zhou Normal University, Hangzhou, Zhejiang, China.
Xuelian FuThe Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Yanhua HaoResearch Center of Public Policy and Management, School of Health Management, Harbin Medical University, Harbin, 150086, Heilongjiang, China.
Heng LiHospital Development institute of Shanghai Jiao Tong University, Shanghai, China.
Linghan ShanResearch Center of Public Policy and Management, School of Health Management, Harbin Medical University, Harbin, 150086, Heilongjiang, China. linghanshan@126.com.
Qunhong WuResearch Center of Public Policy and Management, School of Health Management, Harbin Medical University, Harbin, 150086, Heilongjiang, China. wuqunhong@163.com.
Ye LiResearch Center of Public Policy and Management, School of Health Management, Harbin Medical University, Harbin, 150086, Heilongjiang, China. liye8459@163.com.
Harbin Medical University · CNJiamusi University · CNHangzhou Normal University · CNHeilongjiang Provincial Hospital · CNMinzu University of China · CNShanghai Jiao Tong University · CNYunnan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe vulnerability of cardiovascular disease (CVD) patients' health abilities, combined with the severity of the disease and the overlapping risk factors, leads such people to bear the economic burden of the disease due to the medical services. We estimated the economic burden of CVD and identified the weak link in the design of the medical insurance.

methodsData from 5610 middle-aged and elderly with CVD were drawn from the 2015 wave of "China Health and Retirement Longitudinal Study" (CHARLS). The recommended method of the "World Health Organization" (WHO) was adopted to calculate "catastrophic health expenditure" (CHE), "impoverishment by medical expenses" (IME), and applied the treatment-effect model to analyze the determinants of CHE.

resultsThe incidence of CHE was 19.9% for the elderly families with CVD members, which was 3.6% higher than for uninsured families (16.3%). Families with CVD combined with > 3 other chronic diseases (38.88%) were the riskiest factor for the high CHE in the new rural cooperative medical system (NCMS). Moreover, families with members > 75 years old (33.33%), having two chronic disease (30.74%), and families having disabled members (33.33%), hospitalization members (32.41%) were identified as the high risky determinants for the high CHE in NCMS.

conclusionsElderly with physical vulnerabilities were more prone to CHE. The medical insurance only reduced barriers to accessing health resources for elderly with CVD; however it lacked the policy inclination for high-utilization populations, and had poorly accurate identification of the vulnerable characteristics of CVD, which in turn affects the economic protection ability of the medical insurance. The dispersion between the multiple medical security schemes leads to the existence of blind spots in the economic risk protection of individuals and families.

Indexed as

Cardiovascular DiseasesAgedChinaFinancial StressHealth ExpendituresHumansInsurance, HealthLongitudinal StudiesMiddle AgedCardiovascular diseaseCatastrophic health expenditureChinaHealth policyImpoverishment by medical expenseMedical insurance

Identifiers

PMID33781274
PMCPMC8006647
OpenAlexW3109307877

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.